An increasing number of companies, agencies, individuals, and other parties (collectively “advertisers”) use online advertising to advertise to users of Internet or other network sites or services. An advertiser purchases advertising space from an individual publisher or from an advertising network that distributes advertisements to one or more publishers. A publisher or advertising network may charge the advertiser using one of several methods, including cost-per-click and cost-per-impression. In a cost-per-click system, an advertiser is charged based on the number of times that agents click on its advertisement. An advertiser is not charged when a publisher displays an advertisement to an agent unless the agent clicks on the advertisement. In a cost-per-impression system, an advertiser is charged based on the number of times a publisher displays its advertisement to an agent.
Click fraud, or fraudulent clicks on advertisements, is an issue that concerns advertisers and publishers who use cost-per-click and other payment models. Similarly, impression fraud, or displays of advertisements in situations where the advertisements will not make an impression on a human user, is an issue that concerns advertisers and publishers who use cost-per-impression and other payment models. A hybrid type of fraud is click-through-rate fraud, where both bogus impressions and bogus clicks (and sometimes even bogus conversions) are generated, usually to better hide a click fraud scheme. Click or impression fraud can take a number of forms, including clicks on an advertisement by or displays of an advertisement to competitors, web robots, or users with personal or political agendas. In addition, an adware or clickware virus may install itself on a computer and generate clicks on or impressions of advertisements without the computer user's knowledge. Fraudulent clicks or impressions do not generate revenue or other value for an advertiser; however, the advertiser must pay for the clicks or impressions. Click or impression fraud therefore harms the advertiser by increasing advertising expense, and at the same time harms the publisher by lowering the perceived value of traffic the advertiser receives from the publisher.
In an effort to alleviate the problem of click or impression fraud, there have been attempts to create systems that detect click or impression fraud. Most click or impression fraud detection systems classify each click or impression in a binary manner as either “good” or “bad.” Publishers may use the results of click or impression fraud detection systems in a number of ways. In some cases, a publisher may subtract bad clicks or impressions from the total number of clicks or impressions, charging an advertiser for only good clicks or impressions. Binary click or impression fraud detection systems, however, have several drawbacks. A click or impression may not fall neatly into either the good or bad category, or it may be impossible to determine from the data set that represents the click or impression whether in fact the click or impression is good or bad. A binary approach will therefore unfairly characterize those clicks or impressions that fall somewhere in between. In addition, advertisers may have differing thresholds as to the type of traffic they are willing to accept. One advertiser may consider a user simply viewing its web site as a valuable transaction; another advertiser may only consider a purchase to be a valuable transaction. A binary system does not allow an advertiser to set a level that determines the quality of traffic for which it is willing to pay the publisher. Advertisers and publishers alike would therefore benefit from having a more accurate system of click or impression fraud detection in order to better assess the value of traffic to publisher sites.